Model comparison - Similar price, same tier
GPT-6 Luna vs Qwen3.8-Flash
GPT-6 Luna is from OpenAI and Qwen3.8-Flash is from Alibaba Cloud (Qwen). On list price, GPT-6 Luna charges 33% less than Qwen3.8-Flash for input ($0.10 vs $0.15 per 1M tokens), and Qwen3.8-Flash charges 6% less than GPT-6 Luna for output ($0.47 vs $0.50 per 1M tokens). GPT-6 Luna has a 1,050,000-token context window and Qwen3.8-Flash 1,000,000 tokens; max output is 128,000 and 131,072 tokens per response. GPT-6 Luna was released on September 22, 2026 and Qwen3.8-Flash on August 26, 2026. Both are closed-weights models, available only through an API.
Last verified from each provider's pricing page. All sources
Side-by-side specs
| Spec | GPT-6 Luna | Qwen3.8-Flash |
|---|---|---|
| Provider | OpenAI | Alibaba Cloud (Qwen) |
| Input / 1M tokens | $0.10 | $0.15 |
| Output / 1M tokens | $0.50 | $0.47 |
| Cache read / 1M | $0.01 | $0.016 |
| Cache write / 1M | $0.125 | $0.20 |
| Batch input / 1M | $0.05 | - |
| Batch output / 1M | $0.25 | - |
| Long-context rates above | 272,000 tokens | - |
| Context window | 1,050,000 | 1,000,000 |
| Max output | 128,000 | 131,072 |
| Release date | ||
| Weights | Closed | Closed |
| API model id | gpt-6-luna | qwen3.8-flash |
| AI Gateway id | openai/gpt-6-luna | alibaba/qwen3.8-flash |
| Last verified |
Prices in USD per 1M tokens at each provider's standard first-party rate. A dash means the provider does not bill that item separately or no primary page states it.
What each costs in practice
The same three workloads every model page uses, worked from each model's standard list rates. Swap in your own token counts with the math on each model's page.
| Workload | GPT-6 Luna | Qwen3.8-Flash |
|---|---|---|
| One agent session1M input tokens and 100K output tokens, no caching. | $0.15 | $0.197 |
| A chat app10,000 requests a day at 2K input and 500 output tokens each. | $4.50$135.00 per 30-day month | $5.35$160.50 per 30-day month |
| The same session at a 90% cache hit90% of the input is read from the prompt cache. The one-time cache write premium is not included. | $0.069 | $0.0764 |
Show the math
GPT-6 Luna
- One agent sessionInput: 1M x $0.10 = $0.10Output: 0.1M x $0.50 = $0.05
- A chat appInput: 20M x $0.10 = $2.00Output: 5M x $0.50 = $2.50
- The same session at a 90% cache hitCached input: 0.9M x $0.01 = $0.009Uncached input: 0.1M x $0.10 = $0.01Output: 0.1M x $0.50 = $0.05
Qwen3.8-Flash
- One agent sessionInput: 1M x $0.15 = $0.15Output: 0.1M x $0.47 = $0.047
- A chat appInput: 20M x $0.15 = $3.00Output: 5M x $0.47 = $2.35
- The same session at a 90% cache hitCached input: 0.9M x $0.016 = $0.0144Uncached input: 0.1M x $0.15 = $0.015Output: 0.1M x $0.47 = $0.047
Benchmarks under the same setting
No board in the benchmark directory lists both GPT-6 Luna and Qwen3.8-Flash under the same setting, so there is no like-for-like score to show here.
Set them up in your tools
Step-by-step guides whose official docs list GPT-6 Luna or Qwen3.8-Flash by model id.
- Use OpenAI in AiderLists GPT-6 Luna
- Use OpenAI in ClineLists GPT-6 Luna
- Use OpenAI in Codex CLILists GPT-6 Luna
- Use OpenAI in ContinueLists GPT-6 Luna
- Use OpenAI in GooseLists GPT-6 Luna
- Use OpenAI in OpenCodeLists GPT-6 Luna
- Use OpenAI in Roo CodeLists GPT-6 Luna
- Use OpenAI in ZedLists GPT-6 Luna
- Use Qwen in Claude CodeLists Qwen3.8-Flash
- Use Qwen in Codex CLILists Qwen3.8-Flash
- Use Qwen in Kilo CodeLists Qwen3.8-Flash
- Use Qwen in OpenCodeLists Qwen3.8-Flash
Model pages
FAQ
How do GPT-6 Luna and Qwen3.8-Flash compare on price?
On list price, GPT-6 Luna charges 33% less than Qwen3.8-Flash for input ($0.10 vs $0.15 per 1M tokens), and Qwen3.8-Flash charges 6% less than GPT-6 Luna for output ($0.47 vs $0.50 per 1M tokens). For one agent session of 1M input and 100K output tokens with no caching, that is $0.15 on GPT-6 Luna and $0.197 on Qwen3.8-Flash. Prices are each provider's first-party list rates, verified October 17, 2026 and October 17, 2026.
What are the context windows of GPT-6 Luna and Qwen3.8-Flash?
GPT-6 Luna has a 1,050,000-token context window and Qwen3.8-Flash 1,000,000 tokens; max output is 128,000 and 131,072 tokens per response.
Are GPT-6 Luna and Qwen3.8-Flash open weights?
GPT-6 Luna is closed-weights and is called through OpenAI's API as gpt-6-luna. Qwen3.8-Flash is closed-weights and is called through Alibaba Cloud (Qwen)'s API as qwen3.8-flash.
More comparisons
- Claude Haiku 5.5 vs GPT-6 LunaSimilar price, same tier
- Claude Haiku 5.5 vs Qwen3.8-FlashSimilar price, same tier
- DeepSeek V4.1 Flash vs GPT-6 LunaOpen weights vs closed
- GLM-5.3-Flash vs GPT-6 LunaSimilar price, same tier
- DeepSeek V4.1 Flash vs Qwen3.8-FlashSimilar price, same tier
- GLM-5.3-Flash vs Qwen3.8-FlashSimilar price, same tier
- GPT-5.6 Luna vs GPT-6 LunaSame provider, successor
- Gemini 3.5 Flash-Lite vs Qwen3.8-FlashSimilar price, same tier
Sources
GPT-6 Luna verified from developers.openai.com; Qwen3.8-Flash verified from alibabacloud.com. This page is as current as the older of the two: .
- https://developers.openai.com/api/docs/pricing
- https://www.alibabacloud.com/help/en/model-studio/model-pricing
- https://developers.openai.com/api/docs/models/gpt-6-luna
- https://developers.openai.com/api/docs/changelog
- https://modelstudio.console.alibabacloud.com/ap-southeast-1/model/market/detail/qwen3.8-flash
- https://www.qwencloud.com/models/qwen3.8-flash
- https://www.alibabacloud.com/help/en/model-studio/text-generation-model
- https://www.alibabacloud.com/help/en/model-studio/context-cache
- https://www.alibabacloud.com/help/en/model-studio/newly-released-models
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